{"id":"W4408298380","doi":"10.1016/j.geoen.2025.213830","title":"Forward modeling and data inversion of cased-hole logging parameters for four detectors based on X-ray source","year":2025,"lang":"en","type":"article","venue":"Geoenergy Science and Engineering","topic":"Medical Imaging Techniques and Applications","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Calgary","funders":"","keywords":"Logging; Inversion (geology); Detector; Geology; Remote sensing; Computer science; Physics; Optics; Seismology; Geography; Forestry","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002891526,0.0004287492,0.000303646,0.0003330434,0.0003171527,0.0005402252,0.0007461054,0.0006762646,0.001529724],"category_scores_gemma":[0.0009092872,0.0003765327,0.0004329603,0.0005763634,0.0002619615,0.001060182,0.000316312,0.0006030785,0.0004506793],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004808066,"about_ca_system_score_gemma":0.001419301,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01158332,"about_ca_topic_score_gemma":0.01186639,"domain_scores_codex":[0.9998887,0.00001178812,0.000008029638,0.00003003475,0.00004482537,0.00001673198],"domain_scores_gemma":[0.9997055,0.00008148734,0.00003481389,0.00004350155,0.000124095,0.00001061059],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0004452046,0.0001844459,0.02006362,0.0002029342,0.00006862567,0.0003191741,0.0003534257,0.8011228,0.07055471,0.00375566,0.002029941,0.1008995],"study_design_scores_gemma":[0.00001663488,0.00002539096,0.00278465,0.00000821356,0.00001838274,0.00005284789,0.00005966367,0.9730364,0.02244495,0.0005478092,0.0009807104,0.00002443176],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5021021,0.0003047308,0.4879199,0.0004364212,0.00009666987,0.00008602318,0.001413052,0.00293621,0.004704937],"genre_scores_gemma":[0.9449155,0.0001123402,0.05237553,0.00003366687,0.000005231675,0.00003695792,0.0007848321,0.0001139153,0.001622099],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01158332,"threshold_uncertainty_score":0.02303183,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03137220890272368,"score_gpt":0.2817187634924165,"score_spread":0.2503465545896928,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}